Most existing work on AirComp system assumed spatial-and-temporal independent sensor signals for ease of analysis and optimization [1]}, [2]}, [3]}, [4]}.
However, in practice, different sensor measurements are correlated and the current measurements are normally related to the previous ones.
Spatial-and-temporal sensor signals are commonly considered in the literature of remote state estimation (see e.g. [5]}, [6]}), but have not been considered in AirComp systems to the best of our knowledge.
In particular, unlike the conventional time-independent AirComp system, where only the current received signal is used to estimate the sum signal of the sensors,
the time correlation introduces a new challenge in AirComp system design: how to effectively utilize both the current and the sequence of previously received signals for optimal computation of the sum of current sensor signals?
